load packages

library(tidyverse)
library(palmerpenguins)
library(ggbeeswarm)
library(ggforce)

#remotes::install_github("allisonhorst/palmerpenguins")
# peek at penguins data
#glimpse(penguins)

# create some example data
x <- c(rep("A", 100), rep("B", 100), rep("C", 100))
y <- rnorm(300)

# create a data frame with x, y, and color columns
df <- data.frame(x = x, y = y, color = ifelse(c(1:300) %in% c(5, 10, 15), "Highlighted", "Normal"))

#  geom_point(size = 3) +
# plot the data with points colored by category and highlight
ggplot(df, aes(x = x, y = y, color = color)) +
  scale_color_manual(values = c("Normal" = "black", "Highlighted" = "red")) +
  geom_beeswarm(cex = 1.5) +
  theme_classic()

 #In this script, we use ggplot2 to create a scatter plot with categorical data and highlight some points. We start by creating an example dataset with a categorical variable x and a continuous variable y. We then create a data frame df with x, y, and color columns. The color column is set to "Highlighted" for the points we want to highlight, and "Normal" for the rest.

 #We then use ggplot2 to plot the data. We set x, y, and color to the corresponding columns in df using the aes() function. We use geom_point() to plot the points, and set the size argument to control the size of the points. We use scale_color_manual() to set the colors for the "Normal" and "Highlighted" categories. Finally, we use theme_classic() to set the theme of the plot to a classic theme.

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